For the purpose of this project, we are going to implement a MIP optimizer to model practical bed planning scenarios and solve the patient admission scheduling problem from the hospital’s perspective. Our goal is to assign each patient an appropriate room as soon as possible while reducing the extra cost spent on room transferring. We will achieve this by giving a penalty value for each case of miss-assignment of room, and for every time we fail to accept a patient. Besides, we will also take the extra cost spent on room transfer into account. By minimizing the sum of the overall penalty and extra cost, we will find the optimal solution for managing our patient rooms. Using available data as the input, the MIP model will record situations such as the availability of rooms, priorities, and patients’ requirements for specific medical equipment. These will all become parts of the constraints of the problem. We will try to make this model as applicable as it could be to real-world patient scheduling problems by incorporating more constraints.

https://people.cs.kuleuven.be/~tony.wauters/wim.vancroonenburg/pas/